The way people shop has significantly progresses since the development of the worldwide web (WWW). Consumers can now shop from the convenience of their homes, offices, or while on the road using portable devices. Shopping websites, though differing in nature, allow consumers to purchase goods and services from anywhere in the world over the Internet, often at much lower prices than local merchant sales. From the merchant's perspective, this online availability provides access to a much wider market of potential customers.
Particularly large electronic commerce (e-commerce) websites have typical daily traffic of millions of visitors. Operators of such large e-commerce websites often wish to analyze the traffic visiting the website to determine successes in marketing such as, e.g., which advertising campaigns are successfully, which products sell best, which types of users respond positively to marketing tactics, whether website goals are being met, and so on.
Because operators of e-commerce websites seek to maximize success of marketing, these operators seek to adapt their websites to enhance visitor experiences, thereby increasing traffic. Existing solutions for adapting websites to enhance visitor experiences typically require manual consideration of marketing success or inflexible rules based on overall website performance (e.g., changing content on the website if less than 50% of users interact with the content). Typically, such rules do not allow for immediate adjustment of web content based on user preferences. For e-commerce websites, this inflexibility may result in lost opportunities to sell products.
It would therefore be advantageous to provide a solution that would overcome the deficiencies of the prior art.